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The LINK® TrabecuLink® Tibial Cones are indicated for patients with severe joint diseases with limitation of mobility due to degenerative, rheumatoid or post-traumatic arthrosis or arthritis and joint fractures which disallow an osteosynthetic reconstruction.

The LINK® TrabecuLink® Tibial Cones are indicated for the following conditions:

· Surgeries which require implantation of a total knee endoprosthesis after severe degeneration or bone loss, traumata or other pathologies.

The device is intended for uncemented use.

The LINK® TrabecuLink® Tibial Cones are designed to be used in conjunction with the LINK® Endo-Model® Knee System Standard / Modular / Porex® coated (K143179; K152431) and with the Endo- Model® SL® Knee System (K151008) tibial components. The subject device is intended to fill small to medium bone defects and provide a stable platform for the tibial articulating components.
The tibial cones are manufactured using an EBM (Electron Beam Melting) process with titanium alloy powder (Ti6Al4V, ISO 5832-3). The tibial cones consist of a non-porous bulk interior surface and a trabecular structure made of titanium (LINK® TrabecuLink®) on the external surface.
The LINK® TrabecuLink® Tibial Cones provide cementless fixation to the bone. The subsequently implanted knee endoprosthesis is cemented to the tibial cone.

This document describes the LINK® TrabecuLink® Tibial Cones, a medical device used in total knee replacement surgeries. It does not describe an AI/ML device, and therefore, the information typically requested about AI/ML device studies (such as sample size for test sets, data provenance, number of experts for ground truth, adjudication methods, MRMC studies, standalone performance, training set details, or how ground truth was established for training sets) is not applicable here.

The document focuses on demonstrating the substantial equivalence of the device to legally marketed predicate devices through non-clinical performance testing.

1. Table of Acceptance Criteria and Reported Device Performance

The FDA clearance letter and 510(k) summary do not present formal "acceptance criteria" for performance in a table format with specific numerical targets. Instead, they refer to "non-clinical performance testing and analysis" which demonstrate that the device is "as safe, as effective and substantially equivalent to the predicate device." The "acceptance" is implicitly that the device performs comparably to the predicate devices in these tests.

2. Sample size used for the test set and the data provenance

• Test Set Sample Size: Not applicable. This refers to non-clinical bench testing, not a dataset of patient cases.
• Data Provenance (e.g., country of origin of the data, retrospective or prospective): Not applicable, as this was non-clinical bench testing.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

• Not applicable, as this was non-clinical bench testing. Performance was assessed against engineering and material science standards and comparison to predicate devices, not expert human interpretation.

4. Adjudication method (e.g., 2+1, 3+1, none) for the test set

• Not applicable, as this was non-clinical bench testing.

5. If a multi reader multi case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance

• Not applicable. This is not an AI/ML device, and no MRMC study was conducted.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done

• Not applicable. This is not an AI/ML device.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)

• For non-clinical performance, the "ground truth" or reference for assessment would be established engineering and material science standards, specifications, and direct comparison to the performance characteristics of the predicate devices. There is no biological "ground truth" (like pathology or outcomes data) established for these specific tests, as they are mechanical and material characterizations.

8. The sample size for the training set

• Not applicable. This is not an AI/ML device, and no training set was used.

9. How the ground truth for the training set was established

• Not applicable. This is not an AI/ML device.

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